Results 51 to 60 of about 36,780 (203)
CES Transactions on Electrical Machines and Systems, 2019 Effective storage, processing and analyzing of power device condition monitoring data faces enormous challenges. A framework is proposed that can support both MapReduce and Graph for massive monitoring data analysis at the same time based on Aliyun ...
Hongtao Shen, Peng Tao, Pei Zhao, Hao Ma
doaj +1 more source
Three Algorithms for Parallel Graph Summarization
Expert Systems, Volume 43, Issue 1, January 2026.ABSTRACT Most graph summarization algorithms are tailored to a specific graph summary model and were designed for one‐time computations only, that is, batch‐based computations. We developed a universal approach for parallel graph summarization and three algorithms to compute graph summaries—a batch‐based algorithm for static graphs, an incremental ...
Till Blume +3 more
wiley +1 more source
Hadoop MapReduce scheduling paradigms [PDF]
2017 IEEE 2nd International Conference on Cloud Computing and Big Data Analysis (ICCCBDA), 2017 Apache Hadoop is one of the most prominent and early technologies for handling big data. Different scheduling algorithms within the framework of Apache Hadoop were developed in the last decade. In this paper, we attempt to provide a comprehensive overview over the different paradigms for scheduling in Apache Hadoop.
Johannessen, Roger +2 more
openaire +2 more sources
Observations on Factors Affecting Performance of MapReduce based Apriori on Hadoop Cluster
, 2017 Designing fast and scalable algorithm for mining frequent itemsets is always being a most eminent and promising problem of data mining. Apriori is one of the most broadly used and popular algorithm of frequent itemset mining.
Garg, Rakhi +2 more
core +1 more source
Design of a TSK Rule‐Based Model With Granular Rules and Ensemble Learning in Big Data
Complexity, Volume 2026, Issue 1, 2026.Nowadays, the management and analysis of big data have become major challenges for researchers in the field of data mining. The increasing rate of data generation, along with the need to extract meaningful patterns, highlights the necessity of developing scalable big data analysis methods.
Mohammad Nematpour +4 more
wiley +1 more source
Parallel Cellular Automata Markov Model for Land Use Change Prediction over MapReduce Framework
ISPRS International Journal of Geo-Information, 2019 The Cellular Automata Markov model combines the cellular automata (CA) model’s ability to simulate the spatial variation of complex systems and the long-term prediction of the Markov model.
Junfeng Kang +3 more
doaj +1 more source
Three-Way Joins on MapReduce: An Experimental Study
, 2014 We study three-way joins on MapReduce. Joins are very useful in a multitude of applications from data integration and traversing social networks, to mining graphs and automata-based constructions. However, joins are expensive, even for moderate data sets;
Kimmett, Ben, Thomo, Alex, Venkatesh, S.
core +1 more source
Lightweight Deep Learning Approach for Intelligent Intrusion Detection in IoT Networks
International Journal of Distributed Sensor Networks, Volume 2026, Issue 1, 2026.Intrusion detection system (IDS) is designed to analyze and monitor the network traffic to identify unauthorized access or attacks in an Internet of Things (IoT). IDS assists in protecting IoT devices and networks by recognizing malicious activities and preventing potential breaches.
Srikanth Mudiyanuru Sriramappa +5 more
wiley +1 more source
PUC: parallel mining of high-utility itemsets with load balancing on spark
Journal of Intelligent Systems, 2022 Distributed programming paradigms such as MapReduce and Spark have alleviated sequential bottleneck while mining of massive transaction databases. Of significant importance is mining High Utility Itemset (HUI) that incorporates the revenue of the items ...
Brahmavar Anup Bhat +2 more
doaj +1 more source
Parallel Algorithms for Summing Floating-Point Numbers
, 2016 The problem of exactly summing n floating-point numbers is a fundamental problem that has many applications in large-scale simulations and computational geometry.
Eldawy, Ahmed, Goodrich, Michael T.
core +1 more source